This disclosure relates generally to the field of computer systems. More particularly, but not by way of limitation, it relates to a technique for improving performance monitoring systems.
In a performance monitoring system, a baseline is generally used to compare a metric's current behavior to past normal behavior in order to detect abnormal behavior. A metric's current behavior is considered abnormal if it is outside the normal range defined by the baseline.
Often a configuration change is necessary for an information technology system. A change in configuration may potentially cause a change in behavior in the system which may result in a performance problem. When a configuration change occurs, if a metric goes outside its baseline, an abnormality event is generally generated to alert the system administrator. Some configuration changes may cause other metrics to behave differently as well. However, these behavior changes may not be due to any real change in behavior of the system or the application being monitored. In some circumstances, false positive alerts may be generated in these metrics. In other circumstances, real problems may be obscured and no alert is generated.
Thus, it would be beneficial to provide a mechanism to capture the real problem caused by the configuration change and eliminate the false alarms.